🚪 Touchless Entry-Exit Data Tracking System (TEED-TS)

📖 Overview

The Touchless Entry-Exit Data Tracking System (TEED-TS) is a hygienic, non-contact solution designed to monitor entry and exit movements. It uses Infrared (IR) sensors, the ESP8266 microcontroller, and IoT technologies to provide real-time data tracking while reducing physical contact.

Collected data is visualized through dynamic graphs and stored in CSV format, making it suitable for environments requiring reliable monitoring, such as:

• 🏥 Hospitals
• 🏢 Offices
• 🛒 Retail Spaces
• 🛡️ Security Zones

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✨ Features

• Touchless Monitoring: Tracks entry/exit movements using IR sensors.
• Real-Time Visualization: Displays real-time entry/exit counts via animated bar graphs.
• Data Logging: Saves timestamped data in CSV format for analysis.
• Hygienic and Efficient: Reduces human contact and contamination risk.
• Scalable: Can integrate with larger networks or more complex setups.

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🛠️ Components

🔩 Hardware

Component	Quantity	Description
IR Sensors	4	Detect interruptions in infrared beams.
ESP8266	1	Microcontroller for data processing.
Breadboard	1	For prototyping the circuit.
Jumper Wires	Set	Connect components to the circuit.

💻 Software

1. Arduino IDE: For programming the ESP8266 microcontroller.
2. Python: For data processing and visualization.
   • Libraries used:
     • csv: Handles data logging.
     • time & datetime: For timestamps.
     • matplotlib: For creating animated bar graphs.
     • serial: For serial communication with the ESP8266.

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🚀 How It Works

1. Initialization:

   • The ESP8266 connects to Wi-Fi to sync the current time from an NTP server.

2. Detection:

   • IR sensors monitor movements by detecting interruptions in their beams.

3. Data Processing:

   • The ESP8266 categorizes events as entry or exit and sends the data to a laptop.
   • Timestamped data is logged in a CSV file.

4. Visualization:

   • Real-time bar graphs show ongoing entry/exit counts.
   • Interval-based graphs provide insights every 5 minutes.

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📊 Results

Metric	Performance
Accuracy	~95% in controlled environments.
Sensor Response Time	0.5 seconds (average).
Uptime	100% (during testing).
Test Period Data	98 entries, 96 exits (24 hours).

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🔧 Setup Instructions

Hardware

1. Connect IR sensors to the ESP8266 microcontroller.
2. Use jumper wires and a breadboard for prototyping.
3. Power the ESP8266 and ensure proper wiring.

Software

1. Install Arduino IDE and upload the provided client-side code to the ESP8266.
2. Install Python (3.x) and required libraries using:

   pip install matplotlib pyserial

A practical, precise, and scalable solution for monitoring movements in real-time. This system prioritizes hygiene, efficiency, and data visualization, making it suitable for a variety of environments, including healthcare, retail, and public spaces.

🛠️ Future Improvements

• Replace wired communication with Wi-Fi-based communication: Enhance connectivity and reduce dependency on physical wiring.
• Integrate AI analytics: Analyze movement trends and predict patterns for smarter decision-making.
• Improve sensor calibration: Mitigate interference caused by environmental factors to enhance accuracy.

🏆 Key Benefits

• Hygienic: Reduces contact in sensitive environments.
• Real-Time Insights: Provides live tracking for better monitoring.
• Scalable: Adaptable to various use cases, including large-scale deployments.

🖼️ Visualization Example

Include your data visualization example here (e.g., graphs, charts, or images demonstrating real-time tracking).

📚 References

• Arduino People Counter
• Assessing the ESP8266 Wi-Fi Module
• A Smart Bidirectional Visitor Counter

💡 Conclusion

The Touchless Entry-Exit Data Tracking System (TEED-TS) is designed for environments where hygiene, precision, and efficiency are paramount. Its features and future enhancements ensure adaptability for applications in various sectors, including:

• Healthcare
• Retail
• Public spaces

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🚀 How to Run the Python Script

1. Clone this repository:

   git clone https://github.com/your-repo-name.git
   cd your-repo-name

2. Install required dependencies:

   pip install -r requirements.txt

3. Run the Python script to process and visualize data:

   python script_name.py

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🔧 System Requirements

• Python 3.7+
• Arduino IDE (for microcontroller programming)
• ESP8266 Wi-Fi Module or equivalent
• Sensor hardware

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Feel free to contribute by submitting pull requests or issues!

Screenshots

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Support

For support, email [email protected] .